Bringing Human Cognition to Machines: Introducing Cognitive Edge Devices for the Process Industry

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Abstract

In the era of Industry 4.0 (I4.0), Cyber Physical Production Systems (CPPS) and upcoming industrial transformations, there's a great impulse for smarter, more connected, and adaptable industries. To support this shift, our industrial devices need to be upgraded. They should not only do their usual tasks reliably but also support new technologies like Artificial Intelligence (AI), Machine Learning (ML), Digital Twins (DT), etc. seamlessly. This is where cognition in devices becomes significant. This paper showcases an innovative cognitive system design for edge devices for control, drawing inspiration from the well-established concept of cognitive control. This approach highlights the symphonious existence of conscious (controlled) and unconscious (automatic) processing. The system architecture demonstrates the concurrent processing of real-time tasks, like control loops, field devices, etc., and non-real-time tasks such as AI, ML, Neural Network (NN) models, DT models, etc. within the edge device. This corresponds to the unconscious and conscious cognitive functions in human beings. This paper outlines the characteristics of such cognitive devices. The potential technologies that can help in achieving these characteristics like virtualization, multi-core edge devices, concurrency, etc. have also been explored. Additionally, a proof-of-concept demonstration use case has been presented that exhibits the implementation of the Open Cognitive Control Systems (OCCS) architecture in edge devices. This work sets a stepping stone towards making industrial devices smarter.

Details

OriginalspracheEnglisch
TitelProceedings - 2024 IEEE 22nd International Conference on Industrial Informatics, INDIN 2024
Herausgeber (Verlag)IEEE Xplore
Seitenumfang7
ISBN (elektronisch)9798331527471
PublikationsstatusVeröffentlicht - 12 Dez. 2024
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0003-3954-7786/work/173988065
ORCID /0000-0001-5165-4459/work/173988494
ORCID /0009-0008-7719-8293/work/173988520
ORCID /0000-0003-3368-4130/work/173989150
Mendeley 6ea5a677-f870-3a5d-a547-38c4c7b7b8d3
Scopus 85215515063

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

  • artificial intelligence, cognition, containerization, edge device, process industry, real-time systems